Detailed Configuration

Overview

RtD3 has a number of features that are not required, but can improve the output of a visualisation.

These features include:

• Toggling multiple data sources
• Linking to more detailed estimates
• Plotting flexible geographies

Detailed visualisation

We will prepare the geoData by resolving the USA name conflict between the geoData and estimates.

geoData <- rnaturalearth::ne_countries(returnclass = 'sf')


geoData <- geoData %>%
  mutate(sovereignt = ifelse(sovereignt == 'United States of America', 'United States', sovereignt))

We will also add a second data source (Cases and Deaths) to the rtData.

base_url <- 'https://raw.githubusercontent.com/epiforecasts/covid-rt-estimates/master/national/'

summaryData <- readr::read_csv(paste0(base_url, 'cases/summary/summary_table.csv'), col_types = cols())

rtData <- readr::read_csv(paste0(base_url, 'cases/summary/rt.csv'), col_types = cols())

casesInfectionData <- readr::read_csv(paste0(base_url, 'cases/summary/cases_by_infection.csv'), col_types = cols())

casesReportData <- readr::read_csv(paste0(base_url, 'cases/summary/cases_by_report.csv'), col_types = cols())

obsCasesData <- readr::read_csv(paste0(base_url, 'cases/summary/reported_cases.csv'), col_types = cols())

rtData_death <- readr::read_csv(paste0(base_url, 'deaths/summary/rt.csv'), col_types = cols())

casesInfectionData_death <- readr::read_csv(paste0(base_url, 'deaths/summary/cases_by_infection.csv'), col_types = cols())

casesReportData_death <- readr::read_csv(paste0(base_url, 'deaths/summary/cases_by_report.csv'), col_types = cols())

obsCasesData_death <- readr::read_csv(paste0(base_url, 'deaths/summary/reported_cases.csv'), col_types = cols())

Here, rtData will have two items, “Cases” and “Deaths”. These labels are flexible and are passed to the dataset selector dropdown.

rtData = list('Cases' = list('rtData' = rtData,
                             'casesInfectionData' = casesInfectionData,
                             'casesReportData' = casesReportData,
                             'obsCasesData' = obsCasesData),
              'Deaths' = list('rtData' = rtData_death,
                             'casesInfectionData' = casesInfectionData_death,
                             'casesReportData' = casesReportData_death,
                             'obsCasesData' = obsCasesData_death))

We can also configre a list of URLs to link more detailed estimates.

subregional_ref <- list('Afghanistan' = 'https://epiforecasts.io/covid/posts/national/afghanistan/',
     'Brazil' = 'https://epiforecasts.io/covid/posts/national/brazil/',
     'Colombia' = 'https://epiforecasts.io/covid/posts/national/colombia/',
     'India' = 'https://epiforecasts.io/covid/posts/national/india/',
     'Italy' = 'https://epiforecasts.io/covid/posts/national/italy/',
     'Germany' = 'https://epiforecasts.io/covid/posts/national/germany/',
     'Russia' = 'https://epiforecasts.io/covid/posts/national/russia/',
     'United Kingdom' = 'https://epiforecasts.io/covid/posts/national/united-kingdom/',
     'United States of America' = 'https://epiforecasts.io/covid/posts/national/united-states/')

The data and config are then passed to RtD3::summaryWidget.

## Warning in name_warning_geoData(name_diff): The following names are present
## in the estimates but not in the GeoData: Andorra, Antigua & Barbuda, Aruba,
## Bahamas, Bahrain ... and 33 more.